CODEWITHSUNDEEP
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hammies
hammies

Reputation: 1435

Selecting unique values using user input

I want to select unique values based on user selection from the column header. This is currently under my reactive function.

Example: 

Name    Income    Last Name
John    20        Smith
Sally   44        Smith
John    32        Gold

So there's 2 Johns.

I want something like this:

selItems <- c(input$fromUser, "Income")
unique(selItems$input$fromUser) #totally not correct but this is what I am looking to do

As you can see the user can select all Last names that is unique too. So for all Smiths, how much do they make?

Desired Output if user selects Name

John 52
Sally 44

or if user selects Last Name, then:

Smith 64
Gold  32

Upvotes: 1

Views: 85

Answers (3)

drsh
drsh

Reputation: 66

Just saw the desired output you would like, here is some updated code for that:

NameArray<-data.frame(Name= c("John", "Sally", "John"), Income = c(20,44,32), LastName = c("Smith", "Smith","Gold"))

IncomeArray<-function(SearchColumn,SearchText){ 
    #Name of column, Persons name/income.
    dims<-which(NameArray[,deparse(substitute(SearchColumn))]==deparse(substitute(SearchText)))
    print(NameArray[dims,names(NameArray)!=(deparse(substitute(SearchColumn)))])
}

IncomeArray(Name,John) #Search 'Name' column for 'John' and print out corresponding information.

   Income LastName
1     20    Smith
3     32     Gold

I have left the original code below for completeness

NameArray<-data.frame(Name= c("John", "Sally", "John"), Income = c(20,44,32), LastName = c("Smith", "Smith","Gold"))

IncomeArray<-function(SearchColumn,SearchText, ResultColumn){ 
   #Name of column, Persons name/income, Column name of information of interest.
    dims<-which(NameArray[,deparse(substitute(SearchColumn))]==deparse(substitute(SearchText)))
    print(NameArray[dims,deparse(substitute(ResultColumn))])
}

IncomeArray(Name,John,Income) #Search 'Name' column for 'John' and print out each 'John''s income.
[1] 20 32

The above function might help you out in the cases where you have all the information and just need to access the required columns - little basic but it gets the job done.

Upvotes: 0

r2evans
r2evans

Reputation: 160407

Early attempt, using dplyr:

dat <- data.frame(Name = c("John","Sally", "John"),
                  Income = c(20, 44, 32),
                  LastName = c("Smith", "Smith", "Gold"),
                  stringsAsFactors = FALSE)
library(dplyr)

I'll assume that input is a list provided by some interface such as shiny.

This first batch does no summarizing, just a simple "first record":

input <- list(fromUser = "Name")
dat %>%
  group_by_(input$fromUser) %>%
  slice(1)
# Source: local data frame [2 x 3]
# Groups: Name [2]
#    Name Income LastName
#   <chr>  <dbl>    <chr>
# 1  John     20    Smith
# 2 Sally     44    Smith

input <- list(fromUser = "LastName")
dat %>%
  group_by_(input$fromUser) %>%
  slice(1)
# Source: local data frame [2 x 3]
# Groups: LastName [2]
#    Name Income LastName
#   <chr>  <dbl>    <chr>
# 1  John     32     Gold
# 2  John     20    Smith

If you want something different, insert a sort or max or sum or such:

input <- list(fromUser = "LastName")
dat %>%
  group_by_(input$fromUser) %>%
  summarize(Income = sum(Income))
# # A tibble: 2 x 2
#   LastName Income
#      <chr>  <dbl>
# 1     Gold     32
# 2    Smith     64

Upvotes: 1

MrFlick
MrFlick

Reputation: 206167

Basically you are looking to do some form of aggregation rather than removing duplicates. You have to tell R how to combine redundant rows. The easiest way to do with would be with aggregate. here's an example. First, a more reproducible version of your sample input

dd<-read.table(text="Name    Income    LastName
John    20        Smith
Sally   44        Smith
John    32        Gold", header=T, stringsAsFactors=F)

Then you can use reformualte to build the formulas for use with aggregate()

sel<-"Name"
aggregate(reformulate(sel, "Income"), dd, sum)
#    Name Income
# 1  John     52
# 2 Sally     44    

sel<-"LastName"
aggregate(reformulate(sel, "Income"), dd, sum)
#   LastName Income
# 1     Gold     32
# 2    Smith     64

Upvotes: 3

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